Category: Nancy Elliot

Blog Post 7 – Theoretical Perspectives

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Quite honestly, my hypothesis is based purely on urban legends I have heard over my lifetime. The entire purpose of this introductory study is to see if there is any backbone to this saying. Finding those ecological processes/keywords is the goal of this research. Having read peer-reviewed articles on related subjects and having started my annotated bibliography, I’ve noticed a certain pattern. It is possible that:

  • sunlight is a factor in where the moss is present/absent as it generally is a factor in vegetation growth
  • soil moisture and moisture in general could also be a factor seeing as there are hypotheses out there which connect moisture levels with presence of moss on the northern face of trees
  • presence/absence of water source could be a factor. There are studies out there that demonstrate that water conductivity is a factor in moss growth patterns.

All this will be backed up in my paper with proper citations.

Blog Post 9

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My field experiment was changed many times throughout my time enrolled in this course. I did not know much about ecology or plants prior to this course and my ideas were not easily conducted in a short time without outside assistance. I also struggled with time management; the weather was a large issue as every time I scheduled time to gather data, something in my personal life or the weather would interrupt. As I went back into my study site, I figured out how to gather data in a more efficient and accurate manner. Additionally, I read literature near the end of my research project – in the future I would suggest that others should do research or inquire about the best way to conduct their idea of research. Engaging in the practice of ecology has increased my appreciation for how scientists hypothesize ecological theories.

Blog Post 6 – Data Collection

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I split each study zone in 5 quadrants and counted the trees/moss in each. I believe this means that I did 15 replicates in total. Although I am a bit unsure if replicates are defined the same way in a tabular experimental design. So far, I haven’t had any problems implementing my sampling design. The data seems consistent with the hypothesis. Perhaps I could find a relation between the amount of sunlight & soil moisture to moss growth/direction.

Blog Post 5 – Design Reflections

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The sampling strategy was easy to follow. I just divided up the land, counted the trees in each quadrant, and then took a closer look at the moss and whether it was pointing north or not. I wasn’t surprised by the data, due to the sunlight, it seemed likely that the moss would grow quite a bit on the north side. I believe I will continue to collect data in the same way, it was very efficient. My greatest hurdle was to identify the types of moss. I have no background in Botany and very little experience identifying species. So it took me a while but I think (hope) I figured it out.

Blog Post 4 – Sampling Strategies

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In the virtual forest tutorial, I tried sampling techniques to compare their accuracy.

Haphazard (Area-sample)

  • Total quadrats sampled: 5
  • Area sampled: 500 sq. m
  • Species sampled: 6
  • Total specimens sampled: 39

There was an estimated sampling time of 2 hours 42 minutes. The error percentage for the 2 most common species was 13.9% and 34.2%. The error percentage for the 2 rarest species was 344% and 57%.

Haphazard (Distance-sample)

  • total points sampled: 5
  • species sampled: 5
  • total specimens sampled: 20

There was an estimated sampling time of 59 minutes. The error percentage for the 2 most common species was 42.3% and 28.1%. The error percentage for the 2 rarest species was 72% and 44%.

Systematic (Area-sample)

  • Total quadrats sampled: 5
  • Area sampled: 500 sq. m
  • Species sampled: 6
  • Total specimens sampled: 34

There was an estimated sampling time of 2 hours 39 minutes. The error percentage for the 2 most common species was 4% and 43.6%. The error percentage for the 2 rarest species was 47.1% and 43.6%.

Systematic (Distance-sample)

  • Total points sampled: 5
  • Species sampled: 7
  • Total specimens sampled: 20

There was an estimated sampling time of 59 minutes. The error percentage for the 2 most common species was 13.2% and 12.9%. The error percentage for the 2 rarest species was 51.5% and 11.8%.

From these results I determined that the distance method is the fastest way to sample. When comparing the error percentage of the different strategies for the 2 most common and 2 rarest species, it seems the accuracy does change with species abundance. Generally speaking, the systematic distance sampling method was more accurate than the haphazard one.

Blog Post 3 – Ongoing Field Observations

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I am going to be studying the distribution/abundance of various species of moss (Bryophyta) within the study area and the direction in which they are growing on trees (can they accurately demonstrate cardinal points). I will be collecting distributional data from the “peninsula in the woods”. Although it is, as a whole, a forested area, there definitely are micro-environments which vary significantly from one another. Here is a summary of what I’ve observed:

Area 1: Dense

Sunlight is minimal. Trees at an average of 30cm from each other. Shorter grass. Ground fairly flat. Visible moss and fungi growth.

Area 2: Open

Sunlight is moderate. Trees at an average of 1-2m from each other. Flat land. Tall grass commonly flattened by wildlife. Visible moss and fungi growth.

Area 3: River bank

Sunlight is abundant. Various distance between trees. Ground slanted towards the river. Visible moss and fungi growth.

I hypothesize that moss grows on the Northern face of trees, making it an accurate and reliable source for navigation. Considering my hypothesis, I predict that:

  • There will be an abundance and noticeable amount of at least one species of moss in the studied area.
  • The majority of moss studied will be pointing North.

I believe that the categorical response variable is moss and that the categorical predictor variable is the direction of growth. My experiment is not a manipulative experiment, I won’t be modifying predictor variables to observe the results. I will be conducting a natural, tabular experiment where I will observe the areas as they are, and collect data.

Blog Post 8

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The graph shown above represents the average amount of moisture in soil samples obtained from hilltops and valleys in Valleyview Nature Park. The biggest difficulty I had was figuring out how to create different standard deviation bars on Excel. I decided to organize this data in a figure for ease of interpretation; the rest of my data is summarized in a table not included in this submission.

The average soil moisture content in hilltop samples was 21.95% +/- 1.03%. The average soil moisture content in valley samples was 27.20% +/- 2.22%. Due to limitations of laboratory access and weather, I had to collect the soil samples approximately seven hours after precipitation. Therefore, moisture levels were much higher than I initially anticipated. That being said, my results appear to support what I expected in that soil moisture content was higher in valleys than hilltops.

Blog Post 9

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In reflection I would have done a few more plots and possibly taken one of my biologist friends with me to help in the identification of all the different vegetation species in the area.

I may have ally went out more than a few times and did the multiple sampling dates.  In the early spring when the thistle was first growing, mid summer and early fall to see the difference in the growth of everything in these plots for this area.

 

 

Blog Post 8

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I did have a bit of problems trying to create a single graph that showed all the information that I wanted it to show.  I ended up breaking it up into graphs for each plot.

Plot 1 graph

There was nothing unexpected that I encountered with this project but for future exploration that I would have liked to look at would be to see if there is any grazing in the area that may have happened or the introduction of a biological control to this area to help minimize the growth of the thistle.